Nanocubes

Fast visualization of large spatiotemporal datasets

Nanocubes provides you with real-time visualization of large
datasets. Slice and dice your data with respect to space, time, or some of your data attributes,
and view the results in real-time on a web browser over heatmaps,
bar charts, and histograms. We've used it for tens of billions of data
points: maybe you can push it even farther!

How does it work

The main nanocubes program is a command-line utility that
processes your data and starts a web server to answer query
requests. We
provide Javascript
APIs for visualization. But nanocubes can be used for fast
analysis of your data as well: you can think of it as a very
fast (if somehow limited) database query engine. As an
illustrative example, we have used anomaly detection routines to
query a nanocube and output potential outliers and hotspots.

Details

If you want to know more details about the algorithm behind nanocubes, you can read the research paper that describes it:

Live Demos

Interested? Try the live demos! All of these datasets are
running off of a single machine with 16GB of RAM. For the demos
not tagged as "tablet-friendly", you will need a WebGL capable
browser. We have tested it on Chrome and Firefox, but ourselves
use Chrome and OS X for development.

Nanocubes is Open Source

Team

Why the strange name?

Nanocubes build
on data
cube technology. Until recently, data cubes took a very
large amount of space. This means they could not be stored in
main memory, so their computation and access for large datasets did
not mix well with interactive visualization. Our main
innovation is an algorithm for hierarchical data cubes that has very modest
memory requirements. So it is just like a data cube, but it's
tiny! We thought "nanocube" sounded better than "tinycube".